1. Area of the Art
The present application is in the area of machine intelligence and more specifically in the area of artificial analogs to organic life.
2. Description of Related Art
It is said that the size of the world robotic industry today is around $8 Billion. In Japan, which manufactures more than 50% of the current robots, people expect and dream of a tremendous growth with the personal robots like AIBO® (trademark of the SONY Corporation for personal entertainment robots) and ASIMO™ (pending trademark of the HONDA Corporation for humanoid robots) leading the way. According to forecasts, due to the contribution of robots for personal use, Japanese robotic market will grow to $5.4 Billion in 2005, $17.1 Billion in 2010 and $60 Billion in 2025. Further, it has been predicted that in the year 2040 there will be at least one robot per average family. Yet, the size of the market for such personal robots with intelligence is less than 1% of the total robot market. Ultimately, the robotics industry will be as large as the electronics industry or the automobile industry is today. However, the objective viewpoint holds that those dreams may not come true unless the industry dramatically accelerates development of its robotic technology. Needless to say current digital and analog technologies based on the technology of a Neumann type computer, even with a revised Artificial Intelligence (AI) or neural network the computer is simply inadequate. The robots that people are dreaming of require hardware that includes CPUs that are hundreds of times faster, data communication speeds that are thousands of times faster and memories that are tens of thousand times larger than are available from current technology. In addition, such hardware must be in small packages at affordable prices to make household robots that many people will actually want to have in their homes. Thus, there are high hurdles both technologically and economically that must be overcome. Conventional technologies such as Artificial Intelligence (AI) are unable to surmount these hurdles. AI requires huge memories to store innumerable responses prepared in advance, very fast communication and processing speed to compare such tremendous number of responses with huge volume of constantly incoming information from various sensors and to determine quickly the correct response used to decide the next movement of the robot. With conventional technologies, robots might not work at all in unknown or unpredictable environments.
It is believed that neural network systems can be used to simulate and explain many of the response properties of living organisms. Thus, neural network analogs are considered central in biology. The inventor has studied many neural network systems with an eye to solving the problems of robotics. Current medical science has used neural network solutions to model living body functions. Mechanical functions, language, vision, and other biological functions are amenable to neural network simulations and solutions. Yet, current neural network solutions do not seem to provide the self-organization function—that is growth and reproduction—typical of biological systems. Yet, it should be possible to model the growth, evolution and communication that characterize living systems. The present invention is the outcome of the inventor's efforts to do just that.